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Comment by kristopolous | Hacker News Reader

They aren't the same thing. They are different classes of objects, different tasks. This comparison is kind of silly.

I'd hate my computer to have the memory accuracy or the computational accuracy of my brain. I'd hate to have the creativity and inspiration of a computer.

Delete being such a nontrivial operation is probably a good thing for humans. Copy being imperfect probably has something to do with the phenomenon we call imagination. We use computers because they are complementary, not substitutive.

They're just so fundamentally different.

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When we say the brain has poor computational accuracy, we’re usually talking about the conscious brain we’re aware of. But our low-level motor actions and perceptions, coordinated by the brain, require a lot of precise computation. These low-level brain computations are the thing to compare to AI, not our conscious thinking. Our conscious mind is more like low-precision software running on top of an enormously powerful computer.

> But our low-level motor actions and perceptions, coordinated by the brain, require a lot of precise computation.

But we don't actually do that precise computation though. try repeating any action exactly and you will see some inaccuracy.

no, you will see some variability

Accuracy is a function of variability and bias.

It's unlikely we compute in any conventional sense, the hardware is reality, and is going to exploit every available effect that is energetically efficient.

Letting FPGA's "go" into the analog realm is an interesting window: https://news.ycombinator.com/item?id=21253267

Glial brain cells: https://news.ycombinator.com/item?id=22161192

> But our low-level motor actions and perceptions, coordinated by the brain, require a lot of precise computation.

That accuracy is more likely achieved through fast, analog feedback loops than precise calculation.

Like a giant stack of op-amps. (https://www.computerhistory.org/revolution/analog-computers/...)

How come that in many sports people a good because they basically know everything by heart?

Prof. basball batters, for exampley, are completely baffled by prof. throwers of other sports.

We don't have analog hardware. Nerves are digital. The best we can do with them is pulse-frequency modulation.

I'm not convinced real neurons are just binary summators. But regardless of that, there's also chemical transmission involved, which is an analog thing.

Right, but the end state of all that is "neuron fires" or "neuron doesn't fire", or at best "neuron fires n times per second" - a binary state.

We have some behavior that depends on very exact timing of neuron spikes (e.g. determining direction of sounds by connecting signals from both ears), so that's kind of analog - though it does get reduced into a binary state, in the end either the "detector for offset of x microseconds towards left" fires or not.

How do you even define accuracy for an analog process which solves for unknown formulations? Not saying you can't, but afaik there's no ground to call them accurate. It's certaintly chucking a lot of data in functional ways.

Reaction time and the physical operation of the body are things that seem obvious to me. Try to design a control system for a machine that could replicate a gymnast, for example.

Or a person walking. Boston’s Dynamics is just now making robots near to animals in their walking ability.

Sorry, but in my book responsiveness and functionality doesn't have a thing to do with accuracy (neither does parallelism if I may throw it in there).

Well, I guess I don't know what you mean by accuracy, then. I'm thinking of the accuracy required to hit the right note in a guitar solo, or the accuracy required to time a clean & jerk correctly, or the accuracy required to track a fast-moving object with the eye.

Those things can be surpassed by machines, of course, but if you wanted to design a machine to do all of them? With human efficiency?

> But our low-level motor actions and perceptions, coordinated by the brain, require a lot of precise computation.

Such as?

Identify a ball in a box of items, toss it up in the air, and then catch it. Congratulations, you've just exhibited more computational power than most computers are capable of, including some very precise physics simulation and inverse kinematics.

> memory accuracy

There are individuals with very good memories for all sorts of things, who seem to manage to reconsolidate their memories near-losslessly (at least within the confines of the mental schema they organize said memories into.) Surgeons with anatomy, lawyers and judges with case-law, etc.

At this point I’m convinced that the lossy method humans intuitively reconsolidate memories with, isn’t so much a feature of our mental architecture, as it is a part of the “operating system” we build up on top of our mental architecture—i.e. it’s a skill, something we can learn (or accidentally invent) a better approach to.

> computational accuracy

We compute ratios with extremely high accuracy/precision. Just look at a professional billiards player.

We don’t have a good mind for integer math; but you can translate most integer math problems into ratio problems, and then they become intuitively solvable to humans. (This is basically what geometry is.)

You can even construct memory palaces which are very easy to learn. I still remember them from 10 years ago.

A surgeon might remember anatomy with great accuracy but he is unlikely to remember the details of some case law nearly as well. Our memories are associative, that is how they differ from computers. It's easy for a surgeon to remember anatomy because he has been immersed in it for a long time and it all interconnects, i.e there are a lot of associations to call up the memory. Computers on the other hand could remember 20 facts about anatomy and 20 facts about case law no problem without needing any framework to attach them to.

I remember when I first took a data structures course, learning things like trees and linked lists, I had a total paradigm shift with respect to how I understood my own mind.

I had never really thought about the different ways that data could be organized, and how they perform differently. I figured that since this was so basic to computer science, my own mind couldn't be doing something completely different. It might not be the same in detail as any computer data structure, but it couldn't be completely unrelated either.

I realized that data structures might make information feel different. For example, I can only tell you what the 16th letter of the alphabet is by counting from "A". I can't sing the alphabet song backwards. These are at least qualitatively characteristics of a singly linked list. The same goes for my phone number and my credit card number. I wouldn't be able to dictate them backwards, except by mentally traversing them forwards and then holding the whole number in my conscious memory as I reverse the digits, or if that's too tiring, traversing it forwards multiple times and stopping at different points.

I have many detailed memories of past events, conversations, and trivial facts, but it's hard for me to remember them on command. I need some kind of prompt to point me to the right index where I can retrieve it.

I agree a lot with the interpretation that we have a messy OS that bungles memory management and does lossy compression and a poor job of disk defrag, running on some very impressive hardware.

Recently I was thinking about how my brain answers the question "What's your favorite movie?" and how I can easily answer that question, but it's harder to answer a question like "What's your favorite movie where a gun is fired?"

It seems to me that whenever I watch a movie, if I really liked it, I check my perceived quality of the movie against the quality of my current favorite movie, and if the new movie beats the old favorite, I update the "favorite movie" pointer to point to the new movie. When someone asks "What's your favorite movie?" I just return the name of whatever the favorite_movie points to.

The question of "Favorite movie where a gun is shot" is much harder, I think, because my memories aren't really indexed that way. I can't query by "gun is shot" so I can't get the subset of movies I've seen with gun shots and pick my favorite.

To me, it seems like my brain, at least for movies, has something of a key value store, which I can scan, slowly and imperfectly, but not query with complex questions. Or, maybe, if the queries are too complex they timeout and I don't get back any results.

>The question of "Favorite movie where a gun is shot" is much harder, I think, because my memories aren't really indexed that way. I can't query by "gun is shot" so I can't get the subset of movies I've seen with gun shots and pick my favorite.

And yet as much as yours or mine, or likely most people's memories aren't indexed that way, I bet if you asked enough people you'd find someone who organized their memories in some obscure strange way that would let them answer that question immediately.

>Recently I was thinking about how my brain answers the question "What's your favorite movie?" and how I can easily answer that question,

I can hardly answer that question

I think I need to make a table of all movies I watched, with columns for different quality aspects, and then I could calculate a score for all movies. Then the favorite movie has the highest score.

Then I think a few minutes about the table, before answering that I do not really have a favorite movie

Some very interesting points.

I would like to say that the hardware is a bit of a mess as well. There are weird redundant bits of legacy hardware that aren't required any more, but nobody's bothered to remove them from the system (appendix, wisdom teeth). There are oddly paired systems (genitals combine waste removal with reproduction; the nose combines air filtering with scent detection; the mouth combines food intake and air intake/outlet). And oddly co-dependent systems (lose your sense of smell and your sense of taste takes a significant hit).

What do you mean? That sounds just like a modern CPU to me! :)

A similar example I heard was that a chess grandmaster may be able to take a look at a chessboard with a game in play and memorize the entire board immediately. But only if the board "makes sense" - all the pieces are in positions that could actually be reached in a real game.

If you take those same pieces and rearrange them willy-nilly, then this ability to instantly memorize its layout goes away.

I recall that Jeff Hawkins, when talking about his Hierarchical Temporal Memory ML model (which is supposed to be brain-like), said something like "Nature has spatial and temporal locality. Brains evolved to best store information that also has spatial and temporal locality—in other words, to recapitulate and model the natural world. To the degree that some pattern is akin to one that arises in nature, the brain can store and compute upon it easily. To the degree that a pattern is 'arbitrary'—something that cannot arise in nature—the brain finds it hard to hold into."

The moment-in-time arrangement of chess pieces on a board does not exactly have spatial or temporal locality; but if one has learned a set of mental transformation rules that let that board be translated into a narrative for how it got to be that way—then that narrative is itself something quite natural for the brain's architecture to represent.

I don't see how any of that makes the comparison "silly". It's not like we have so many instances of computer paradigms to go around comparing.

It's like measuring a gun in units of swords. You can achieve similar ends but they aren't the same. Or the companionship of a spouse in units of pets. The fundamental unit is at the affect level, not the application. That's a very important distinction.

Any model comparing the application then is fundamentally misinformation.

It's even worse because it suggests an equivocation is possible. As if you can get X units of dogs as a substitute for Y units of spouse. You just have to find the magic ratio!

Wrong framings can stick people in insolvable problems well, sometimes for generations. It's really bad.

They're fundamentally different and pretending otherwise is just going in the one of the most useless directions possible

Exactly. We shouldn't be so arrogant in thinking the modern computer is the same thing as a human brain.

This comparison is pointless. The human brain is beyond comprehension. Computers are just logic calculators.

>The human brain is beyond comprehension.

Many things in the world were beyond our comprehension, until they weren't. I see no reason why the human brain's inner workings should evade our understanding indefinitely.

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